Association for Computing Machinery
Data privacy focuses on the protection of data against possible disclosures. Because of that, disclosure risk assessment is a main concern and there are several approaches for its definition. The authors provide a formal framework for re-identification in general. They define n-confusion as a concept for modeling the anonymity of a database table and they prove that n-confusion is a generalization of k-anonymity. Finally they present an example to illustrate how this result can be used to augment local variance in k-anonymous protected data.